Reattribution to Mind-Brain Processes and Recovery From Chronic Back Pain

Importance In primary chronic back pain (CBP), the belief that pain indicates tissue damage is both inaccurate and unhelpful. Reattributing pain to mind or brain processes may support recovery. Objectives To test whether the reattribution of pain to mind or brain processes was associated with pain relief in pain reprocessing therapy (PRT) and to validate natural language–based tools for measuring patients’ symptom attributions. Design, Setting, and Participants This secondary analysis of clinical trial data analyzed natural language data from patients with primary CBP randomized to PRT, placebo injection control, or usual care control groups and treated in a US university research setting. Eligible participants were adults aged 21 to 70 years with CBP recruited from the community. Enrollment extended from 2017 to 2018, with the current analyses conducted from 2020 to 2022. Interventions PRT included cognitive, behavioral, and somatic techniques to support reattributing pain to nondangerous, reversible mind or brain causes. Subcutaneous placebo injection and usual care were hypothesized not to affect pain attributions. Main Outcomes and Measures At pretreatment and posttreatment, participants listed their top 3 perceived causes of pain in their own words (eg, football injury, bad posture, stress); pain intensity was measured as last-week average pain (0 to 10 rating, with 0 indicating no pain and 10 indicating greatest pain). The number of attributions categorized by masked coders as reflecting mind or brain processes were summed to yield mind-brain attribution scores (range, 0-3). An automated scoring algorithm was developed and benchmarked against human coder–derived scores. A data-driven natural language processing (NLP) algorithm identified the dimensional structure of pain attributions. Results We enrolled 151 adults (81 female [54%], 134 White [89%], mean [SD] age, 41.1 [15.6] years) reporting moderate severity CBP (mean [SD] intensity, 4.10 [1.26]; mean [SD] duration, 10.0 [8.9] years). At pretreatment, 41 attributions (10%) were categorized as mind- or brain-related across intervention conditions. PRT led to significant increases in mind- or brain-related attributions, with 71 posttreatment attributions (51%) in the PRT condition categorized as mind- or brain-related, as compared with 22 (8%) in control conditions (mind-brain attribution scores: PRT vs placebo, g = 1.95 [95% CI, 1.45-2.47]; PRT vs usual care, g = 2.06 [95% CI, 1.57-2.60]). Consistent with hypothesized PRT mechanisms, increases in mind-brain attribution score were associated with reductions in pain intensity at posttreatment (standardized β = −0.25; t127 = −2.06; P = .04) and mediated the effects of PRT vs control on 1-year follow-up pain intensity (β = −0.35 [95% CI, −0.07 to −0.63]; P = .05). The automated word-counting algorithm and human coder-derived scores achieved moderate and substantial agreement at pretreatment and posttreatment (Cohen κ = 0.42 and 0.68, respectively). The data-driven NLP algorithm identified a principal dimension of mind and brain vs biomechanical attributions, converging with hypothesis-driven analyses. Conclusions and Relevance In this secondary analysis of a randomized trial, PRT increased attribution of primary CBP to mind- or brain-related causes. Increased mind-brain attribution was associated with reductions in pain intensity.


Introduction
Beliefs that pain is due to peripheral pathophysiology (eg, a bulging disc, osteoarthritis) are common.
Yet, peripheral findings are often incidental in nature and not the predominant cause of symptoms.
2][3] For these patients, the inaccurate belief that pain signifies tissue damage may promote fear, avoidance, disuse, and the persistence of pain. 4,5 recently developed pain reprocessing therapy (PRT), a novel psychological treatment aiming to help patients reframe primary chronic pain as caused by nondangerous, reversible brain pathways.PRT presents primary pain as what could be described as a "false alarm" of tissue damage that can be reversed.PRT demonstrated promising efficacy in a 2022 clinical trial 6 of 151 adults with low-moderate severity chronic back pain: 66% of participants randomized to PRT were pain-free or nearly so at posttreatment, as compared with fewer than 20% of placebo and usual care controls.
Better understanding the psychological mechanisms of PRT is critical.
][9][10] Patients' symptom attributions have rarely been investigated in chronic pain, although extant work suggests that attributions center on peripheral tissue pathology. 11,12This is understandable: imaging studies often reveal incidental findings (eg, small disc bulges) that can be easily misinterpreted as causal of pain, and pain is naturally associated with injury, rendering other attributions unintuitive. 13,14We hypothesized that the reattribution of pain to mind-or brain-related processes: (1) occurs in PRT, and (2) is associated with pain reduction.
We measured pain attributions before and after treatment using open-ended, free-text responses asking participants to describe the perceived causes of pain in their own words.Natural language approaches complement other valuable measurement tools.Relative to multiple choiceformat questions, they provide a minimally constrained approach to studying how patients spontaneously think, capturing a broader set of concepts and beliefs than otherwise possible.
Relative to qualitative analyses, they are quantitative and scalable (easily applied to large text data sets, eg, social media, electronic health record data).Natural language methods have been valuable in several psychiatric applications, including dimensional phenotyping 15 and prediction of treatment response, 16 but we are not aware of previous applications to symptom attributions.

Methods
The pain attribution data presented here were collected as part of a preregistered clinical trial (NCT03294148) conducted from 2017 to 2019, with the current analyses conducted from 2020 to 2022.Primary outcomes have been previously reported, 6 but not the attribution data.We provide a brief overview of the trial design here, with full details available in the prior publication and

Participants
Participants aged 21 to 70 years with back pain for at least half the days of the last 6 months and

Interventions
In the PRT group, participants completed a 1-hour telehealth session with a physician followed by 8 individual 1-hour sessions with a therapist twice weekly for 4 weeks.Treatment assessed centralized vs peripheral contributions to pain and provided education on mind and brain generators of chronic pain, substantiated by personalized supporting evidence (eg, spatial spread of symptoms, history of multiple somatic symptoms). 18Treatment aimed to shift pain attributions using guided somatically focused reappraisal exercises and by promoting insight into links between emotional or psychological states and pain.A further description of PRT is provided in the eMethods in Supplement 2.
Participants in the open-label placebo group watched 2 videos 19 describing how placebos can powerfully relieve pain even when known to be inert and received a subcutaneous injection openly described as saline into the back during an empathic, validating clinical encounter in an orthopedic medical center.This intervention did not directly target pain attributions.Participants in the usual care group agreed to continue current care as usual and not start new treatments during study participation.

Measures
Participants completed self-report measures at baseline (prerandomization) and posttreatment using an electronic database (REDCap) and masked research assistants.Attributions were collected using an adapted form of the final item of the Illness Perceptions Questionnaire, 20 instructing participants to "please list in rank-order the 3 most important factors that you believe caused your pain" in a short-answer format.Pain intensity was measured as last-week average pain (0 to 10 numerical rating, with 0 indicating no pain and 10 indicating greatest pain), using the first item of the Brief Pain Inventory Short Form. 21Questionnaire measures of pain beliefs included: (1) the Tampa Scale of Kinesiophobia (TSK-11), 22 which has a 2-factor structure measuring activity avoidance and harm beliefs 23,24 ; (2) the Pain Catastrophizing Scale (PCS), 25 assessing pain-related amplification, rumination, and helplessness; and (3) the Survey of Pain Attitudes (SOPA) 2-item Emotions subscale, 26 assessing perceived influences of stress and emotion on pain.

Analyses
We conducted 4 sets of analyses of the free-text pain attributions: (1) categorization of the attributions by human coders, with the total number of attributions assigned to a category reflecting mind or brain processes quantified as mind-brain attribution scores; (2) computing the frequencies of specific words used in attributions; (3) application of a data-driven (unsupervised) text scaling algorithm identifying the principle semantic dimensions underlying the attributions data; and (4)

Human Coder-Derived Categorization
The authors reviewed the free-text attributions while masked to treatment condition and time point and developed conceptually coherent categories of attributions based on this review of the data.
Two masked authors then assigned each participant-generated attribution to a category, with disagreement resolved by discussion.Three categories were considered by the authors as mind-or brain-related.We tallied how many of the 3 attributions provided by each participant were assigned to one of these categories, yielding a mind-brain attribution score for each participant at each time point ranging from 0 (no mind-or brain-related attributions) to 3 (all attributions mind-or brain-related).
Using these mind-brain attribution scores, we tested for (1) their association with questionnaire measures of pain beliefs (TSK-11, PCS, SOPA-emotions) and demographic attributes at baseline, ( effects of PRT vs control conditions to measure target engagement, and (3) for associations with changes in pain intensity, harm beliefs, or activity avoidance in PRT, investigating whether reattribution might be a psychological mechanism of PRT.We additionally investigated longer-term effects of reattribution, examining associations between changes in mind-brain attribution scores and pain intensity at 1-year follow-up.Finally, we conducted a longitudinal mediation analysis testing whether the effects of PRT vs combined controls on 1-year follow-up pain intensity was mediated by pre-to-posttreatment changes in mind-brain attribution scores.Statistical model details are provided in the eMethods in Supplement 2.

Word Frequency Changes
We identified the specific words with the largest pre-to-posttreatment changes in frequency within the PRT condition.The word counts reflect how often participants used particular words in their attributions.This complemented the human coder-derived categorizations in 2 ways: it provided an objective outcome (not based on human coder decisions), and it provided a finer-grained outcome relative to the coarser categories.

Text Scaling
Text-scaling algorithms characterize the semantic structure of collections of documents, identifying principal dimensions based on patterns of word cooccurrence.We used an algorithm including regularization methods that provides enhanced reliability for short documents. 27,28Text scaling is commonly used to identify ideological dimensions underlying political texts (eg, political left vs right); we hypothesized that a text-scaling algorithm might identify a mind-brain vs structuralbiomechanical dimension underlying pain attributions and that post-PRT participants would be further toward the mind-brain end of such a dimension (eMethods in Supplement 2).

Automated Attribution Scoring Algorithm
We sought to develop an automated, scalable method for scoring whether attributions were mindor brain-related.Five expert clinicians who had not seen the participant-provided attributions generated words that they would consider mind-or brain-related, which we preprocessed using standard methods (eMethods in Supplement 2).A word-counting algorithm computed whether each attribution contained words from the expert-derived list (yes-no scoring), yielding an algorithmically derived mind-brain attribution score ranging from 0 (no attributions contained expert-derived mind or brain words) to 3 (all 3 attributions contained expert-derived mind or brain words).We benchmarked the performance of the automated word-counting algorithm relative to the human coder-derived mind-brain attribution scores using Cohen κ (eMethods in Supplement 2).In contrast to text scaling, the automated algorithm was trained independently of the data and provided scores on the same scale as the manual coding approach, enabling direct comparison and validation.[10.17]) at pretreatment, with mean (SD) CBP duration of 10.0 (8.9) years.Preexisting spinal imaging was available in 20 patients in the PRT condition, all of whom had at least 1 spinal anomaly, with a median of 4 anomalies per participant. 6Full sample demographics are available in Ashar et al. 6 All participants provided 3 substantive or meaningful pain attributions, except for 1 participant (who wrote "???").Attributions ranged in length from 1 to 39 words, with a mean (SD) of 3.11 (3.26)   words.Of 891 attributions coded, only 38 (4%) were categorized discrepantly between coders.Each participant's mind-brain attribution score was computed as the number of attributions assigned by the human coders to a mind-or brain-related category (stress, psychological, and brain).

JAMA Network Open | Psychiatry
Mind-brain attribution scores ranged from 0 to 3 and were low at baseline (mean, 0.27; median, 0), which indicated predominantly non-mind or brain attributions (Figure 2).At baseline, mind and brain attribution scores were positively correlated with a stronger perceived influence of stress and emotion on pain (SOPA Emotion subscale) (r 149 = 0.22; P = .007),were positively correlated with pain intensity (r 149 = 0.17; P = .03),and were marginally higher for women than men (d = 0.28; P = .07).Baseline mind-brain attribution scores were not correlated with harm beliefs or activity avoidance (TSK-11), pain catastrophizing (PCS), age, or duration of back pain.
Increases in mind-brain attribution scores were associated with decreases in pain intensity at posttreatment in the PRT condition (standardized β = −0.25,t 127 = −2.06;P = .04),consistent with hypotheses (Figure 3B); interactions for condition × change in mind-brain attribution score on pain intensity were not significant.Examining simple correlations, pre-to-posttreatment changes in mindbrain attribution scores and pain intensity were r 133 = −0.52 (P < .001)across the full sample and r 42 = −0.28(P = .06)within the PRT condition, corresponding to roughly 9% of variance explained by changes in mind-brain attribution scores within the PRT condition.These effects were largely maintained when examining pain intensity at 1-year follow-up, with standardized β = −0.33Mind-brain attribution scores were computed by counting how many of the 3 attributions provided by participants were categorized as psychological, stress, or brain by coders masked to treatment condition and time point (range: 0-3, with higher scores indicating more mind or brain attributions).A, PRT produced large pre-to-posttreatment increases in mind-brain attribution scores relative to placebo and usual care.B, Within the PRT condition, pre-to-posttreatment increases in mind and brain attributions were significantly associated with decreases in pain intensity.

Text Scaling
The first principal component identified by the data-driven text scaling algorithm ranged from predominantly structural or mechanical words to predominantly mind and brain words (eg, from car and scoliosis to anxiety and stress) (Figure 4).

Automated Attribution Scoring Algorithm
Agreement between the automated word-counting algorithm and the human coder-derived scores was substantial at posttreatment (Cohen κ = 0.68 [95% CI, 0.52-0.84];Z = 8.38; P < .001),and moderate at pretreatment (Cohen κ = 0.42 [95% CI, 0.17-0.67];Z = 3.27, P = .001).Examination of confusion matrices revealed that disagreement was driven primarily by the automated algorithm considering attributions as mind-or brain-related when human coders did not.For example, childhood injury was miscategorized as mind and brain-related by the automated algorithm due to the presence of the word childhood in the expert-derived list.

Discussion
We investigated how participants think about the underlying causes of their chronic back pain in their own words, and we tested how changes in pain attributions support pain reductions in pain reprocessing therapy (PRT).2][3] Relative to control conditions, PRT led to large increases in mind-and brain-related attributions, demonstrating target engagement.Increases in mind and brain attributions were associated with reductions in pain intensity at posttreatment and mediated the effects of PRT on 1-year follow-up pain intensity, consistent with hypothesized mechanisms of PRT.

Figure 2
Figure 2. Pain Attribution Category Prevalence

(
t 108 = −2.42;P = .02)and simple correlations of r 114 = −0.44 (P < .001)across the full sample and r 34 = −0.25 (P > .99)within the PRT condition.Changes in mind-brain attribution scores partially mediated the effects of PRT vs control on pain intensity at 1-year follow-up (standardized β = −0.35[95% CI, −0.07 to −0.63]; P = .05).Increases in mind-brain attribution scores were associated with decreased harm beliefs and activity avoidance (TSK-11) at posttreatment in the PRT condition, standardized β = −0.27(t 127 = −2.41;P = .02),consistent with hypotheses; interactions for condition × change in mind-brain attribution scores interactions were not significant.Pre-to-posttreatment changes in mind-brain attribution scores and pre-to-post changes in harm beliefs or activity avoidance were correlated r 133 = −0.57(P < .001) in the full sample and r 42 = −0.37 (P = .01)within the PRT condition.Increases in mind-brain attribution scores were similarly associated with decreased catastrophizing (eResults in Supplement 2).

Figure 3 .
Figure 3. Effects of Pain Reprocessing Therapy (PRT) on Patients' Attributions Regarding the Underlying Causes of Chronic Back Pain

Table .
Categories of Patient Attributions Regarding Perceived Causes of Pain a Categories were derived from discussion among authors masked to treatment condition and time point analyses.Prevalence rates for each category are shown in Figure2and eTable 1 in Supplement 2.

on 09/30/2023 Word Frequency Changes The
Reattribution to Mind-Brain Processes and Recovery From Chronic Back Pain word with the largest increase in prevalence in the PRT condition was anxiety.Several emotionrelated words (eg, fear, feelings, emotion, people) and neurobiological words (neural, pathways) were absent at baseline but present in PRT participant attributions at posttreatment, reflecting the introduction of a novel vocabulary.PRT participants decreased their use of words reflecting biomedical attributions, including activity, weight, disc, and sport (eTable 2 in Supplement 2).
Downloaded From: https://jamanetwork.com/ 4. Scaling Analysis of Posttreatment Attributions Identifying Semantic Connections Underlying Free-Text AttributionsThe first dimension ranged from primarily biomechanical words to primarily mind-or brainrelated words.The location of each participant's posttreatment attributions in the first dimension is shown, with 95% CIs around each condition's mean location (top).Participants randomized to PRT vs placebo and usual care were significantly further toward the mind and brain end of the first dimension, and scores further toward the mind and brain end of the first dimension were associated with greater pain reduction.46.MoraisCA, Newman AK, Van Dyke BP, Thorn B. The effect of literacy-adapted psychosocial treatments on biomedical and biopsychosocial pain conceptualization.J Pain. 2021;22(11):1396-1407.doi:10.1016/j.jpain.2021.Number of Attributions in Each Category for Each Group at Each Timepoint eTable 2. Words With Largest Pre-to-Posttreatment Changes in Frequency Among Participants Randomized to PRT, Derived From Participants' Attributions Regarding Causes of Pain eFigure.Word Clouds Showing Common Words Used in Participants' Pain Attributions